> This page is for version v1.3 (default).
> For other versions, use one of these documentation indexes:
> - v1.3 (default): https://docs.twelvelabs.io/v1.3/llms.txt

> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.twelvelabs.io/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.twelvelabs.io/_mcp/server.

# Snowflake - Multimodal Video Understanding

> This integration combines the TwelveLabs Embed API with Snowflake Cortex to create advanced video search and summarization workflows.

![](/_fern-img/5a1064ab92bd267eda225fb608af888728fd6a5d48d14b3069b23f86bfded255.webp)

**Summary**: This integration combines TwelveLabs' [Embed API](/docs/guides/create-embeddings) with [Snowflake Cortex](https://docs.snowflake.com/en/user-guide/snowflake-cortex/overview) to create advanced video search and summarization workflows.

**Description**: This integration enables you to generate multimodal video embeddings using TwelveLabs' Embed API and store them in Snowflake tables with the `VECTOR` datatype for efficient similarity searches. By utilizing Snowflake Cortex Complete for summarization and other AI capabilities, you can build powerful applications such as semantic video search, content recommendations, and more.

**Code explanation**: Our blog post, [Integrating TwelveLabs Embed API with Snowflake Cortex for Multimodal Video Understanding](https://www.twelvelabs.io/blog/twelve-labs-and-snowflake-cortex), provides a detailed walkthrough of the integration process.